By clicking the "Accept" button or continuing to browse our site, you agree to first-party and session-only cookies being stored on your device to enhance site navigation and analyze site performance and traffic. For more information on our use of cookies, please see our Privacy Policy.
This paper proposes a framework for assessing whether misspecified decision
makers would be willing to pay for information that can potentially
make them less misspecified. We introduce a prior-free approach, based on
“constrained” maximal regret, to derive an upper bound on the subjective
assessment of potential gains from acquiring a more accurate model. The
constraint stems from the information currently available to the decision
maker. We apply our approach to three prominent models of misspecified
beliefs: coarse expectations, causal misperceptions and sampling equilibria.